import os
import numpy as np
from specvae.vae import BaseVAE
import specvae.dataset as dt
import specvae.utils as utils
import matplotlib.pyplot as plt
import seaborn as sns
# Parameters
dataset = "MoNA"
# model_name = "jointvae_20-800-200-50-3-50-200-800-20_01 (11-01-2022_23-10-10)"
# model_name = "betavae_capacity_20-800-200-50-3-50-200-800-20_01 (24-12-2021_01-50-12)"
# model_name = "betavae_capacity_100-400-100-3-400-100_01 (24-12-2021_11-06-17)"
# model_dir = "D:\\Workspace\\SpecVAE\\.model\\MoNA\\jointvae\\jointvae_20-800-200-50-3-50-200-800-20_01 (11-01-2022_23-10-10)"
# model_dir = "d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_capacity_20-800-200-50-3-50-200-800-20_01 (24-12-2021_01-50-12)"
# model_dir = "d:\\Workspace\\SpecVAE\\.model\\HMDB\\betavae_capacity_nextron\\betavae_capacity_20-1600-2-1600-20_02 (24-12-2021_18-27-38)"
model_dirs = [
# MoNA
## BetaVAE
### Best
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_20-800-200-50-3-50-200-800-20_01 (24-12-2021_01-50-12)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_20-400-100-3-400-20_02 (24-12-2021_03-34-34)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_20-1600-3-1600-20_03 (24-12-2021_00-17-31)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_20-800-3-800-20_04 (24-12-2021_00-25-10)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_20-100-3-90-100-20_05 (24-12-2021_03-01-19)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_50-400-3-100-400-50_06 (24-12-2021_06-19-49)",
### Beta
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_01 (24-12-2021_09-13-36)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_02 (24-12-2021_09-15-11)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_03 (24-12-2021_09-29-26)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_04 (24-12-2021_09-29-36)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_05 (24-12-2021_09-06-14)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_06 (24-12-2021_09-05-10)",
### BetaVAE Score
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-400-100-3-400-100_01 (24-12-2021_11-06-17)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-800-100-3-800-100_02 (24-12-2021_10-59-29)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-400-200-50-3-50-200-400-100_03 (24-12-2021_09-47-19)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-1600-3-1600-100_04 (24-12-2021_08-02-44)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-400-100-3-400-100_05 (24-12-2021_10-57-01)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-400-100-3-100-400-100_06 (24-12-2021_08-41-33)",
### FactorVAE Score
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-100-90-50-3-50-90-100-100_01 (24-12-2021_09-48-37)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-1600-100-3-1600-100_02 (24-12-2021_10-51-41)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-800-100-3-800-100_03 (24-12-2021_11-16-41)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-1600-3-1600-100_04 (24-12-2021_08-02-44)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-400-200-50-3-50-200-400-100_05 (24-12-2021_09-23-23)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-1600-100-3-100-1600-100_06 (24-12-2021_08-25-38)",
]
device, cpu = utils.device(use_cuda=True)
GPU device count: 1 Device in use: cuda:0
# print("Load model: %s..." % model_name)
def load_model(path, device):
model_path = os.path.join(path, 'model.pth')
model = BaseVAE.load(model_path, device)
model.eval()
return model
# labels = ['ionization_mode_id', 'collision_energy', 'total_exact_mass', 'precursor_mz', 'instrument_type_id', 'precursor_type_id', 'superclass_id', 'class_id']
if dataset == 'MoNA':
labels = ['collision_energy', 'total_exact_mass']
base_path = utils.get_project_path() / '.data' / 'MoNA'
metadata_path = base_path / 'MoNA_meta.npy'
elif dataset == 'HMDB':
labels = ['collision_energy']
base_path = utils.get_project_path() / '.data' / 'HMDB'
metadata_path = base_path / 'HMDB_meta.npy'
metadata = None
if os.path.exists(metadata_path):
metadata = np.load(metadata_path, allow_pickle=True).item()
# metadata['precursor_type_id']
def load_data(target_column):
# data_path = base_path / ('visualization_%s.csv' % target_column)
data_path = base_path / ('%s_full.csv' % dataset)
df = dt.Spectra.open(data_path)
return df
def preload_data_as_tensor(df, input_columns, types, transform):
# columns = model.config['input_columns']
columns = input_columns
# types = model.config['types']
data = dt.Spectra.preload_tensor(
device=device, data_frame=df[columns + ['id']], transform=transform, limit=-1, types=types, do_print=False)
return data
def evaluate_model(model, df, data):
print("Encode N=%d instances from %s dataset..." % (data['id'].shape[0], dataset))
X, ids = data['spectrum'], data['id'] # TODO: handle the case for concatanated input
Xrecon, z, latent_dist = model.forward_(X)
print(z.shape)
data_np = {}
data_np['X'] = X.data.cpu().numpy()
data_np['Xrecon'] = Xrecon.data.cpu().numpy()
data_np['z'] = z.data.cpu().numpy()
data_np['ids'] = ids
data_np['ionization_mode_id'] = df['ionization_mode_id'].to_numpy()
data_np['collision_energy'] = df['collision_energy'].to_numpy()
# data_np['images'] = df['images'].to_numpy()
return data_np
# import json
# import pandas as pd
# import plotly.express as px
# n_dim = model.latent_dim
# with open(os.path.join(model_dir, 'history.json')) as history:
# history_logs = json.load(history)
# steps = np.array(history_logs['kldiv_cont_0'])[:,0]
# colors = ['kldiv_cont_%d' % dim for dim in range(n_dim)]
# kldivs = dict(zip(colors, [np.array(history_logs['kldiv_cont_%d' % dim])[:,1] for dim in range(n_dim)]))
# kldivs['steps'] = steps
# df = pd.DataFrame(data=kldivs)
# fig = px.line(df, x='steps', y=colors, title='KL Divergence per each cont. dimension')
# fig.show()
from IPython.display import display
df = load_data("")
df = df[
(df['collision_energy'] == 35) &
(df['total_exact_mass'] <= 800) &
(df['instrument_type_id'] == metadata['instrument_type_id']['labels'].index('ESI-QFT')) &
(df['ionization_mode_id'] == 1) &
(df['precursor_type_id'] == 2)
]
# df = df[
# (df['collision_energy'] <= 100) &
# (df['total_exact_mass'] >= 248.14) & (df['total_exact_mass'] <= 249) &
# (df['instrument_type_id'] == metadata['instrument_type_id']['labels'].index('ESI-QFT')) &
# (df['ionization_mode_id'] == 1) &
# (df['precursor_type_id'] == 2)
# ]
display(df.groupby('total_exact_mass')['total_exact_mass'].value_counts())
display(df.groupby('collision_energy')['collision_energy'].value_counts())
display(df)
total_exact_mass total_exact_mass
100.063663 100.063663 1
101.084064 101.084064 1
102.042927 102.042927 1
103.063329 103.063329 1
108.021129 108.021129 1
..
793.424856 793.424856 1
794.445257 794.445257 2
796.257850 796.257850 1
796.424521 796.424521 1
798.221858 798.221858 1
Name: total_exact_mass, Length: 1299, dtype: int64
collision_energy collision_energy 35.0 35.0 2020 Name: collision_energy, dtype: int64
| Unnamed: 0 | spectrum | SMILES | instrument | library | author | publication | structural_key | CASMI | split | ... | instrument_type_id | precursor_type_id | kingdom | superclass | class | subclass | kingdom_id | superclass_id | class_id | subclass_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 6 | 6 | 50.764058:0.030004 50.861465:0.032838 50.99858... | O=C1OC=2C=C3OC(CC3=CC2C=C1C(C=C)(C)C)C(OC(=O)C... | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | AWMHMGFGCLBSAY | NaN | train | ... | 0 | 2 | Organic compounds | Phenylpropanoids and polyketides | Coumarins and derivatives | Furanocoumarins | 1 | 18 | 70 | 184 |
| 39 | 39 | 50.093486:0.010973 54.760810:0.010155 54.85744... | OC1CC(=C)C2CC(CCC2(C)C1)C(O)(C)C | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | XZXBGGYJQALVAW | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Prenol lipids | Sesquiterpenoids | 1 | 6 | 198 | 420 |
| 56 | 56 | 51.377261:0.015250 51.667789:0.017698 52.09552... | O=C(OC1OC(COC(=O)C(=C)C(O)CO)C(O)C(O)C1O)C=CC=... | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | MYWZGSROPRXVPM | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Saccharolipids | NaN | 1 | 6 | 233 | -1 |
| 80 | 80 | 50.130802:0.007823 50.143618:0.006986 50.25242... | O=C(O)C1=COC(OC2OC(CO)C(O)C(O)C2O)C3C(=CCC13)C... | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | VTQUQEWGIJRVHB | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Prenol lipids | Terpene glycosides | 1 | 6 | 198 | 446 |
| 106 | 106 | 50.303740:0.030832 50.373785:0.030336 50.53019... | O=C1OC=C(C=C1)C2CCC3(O)C4CCC5=CC(OC6OC(CO)C(OC... | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | KKOLMSSIDZXPLS | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Steroids and steroid derivatives | Steroid lactones | 1 | 6 | 238 | 429 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 120095 | 120095 | 50.147354:0.008438 51.209227:0.008929 52.42235... | O=C1C=2C=CC=CC2OC3=CC=C(OC)C=C31 | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | DVZCOQQFPCMIPO | NaN | train | ... | 0 | 2 | Organic compounds | Organoheterocyclic compounds | Benzopyrans | 1-benzopyrans | 1 | 14 | 43 | 11 |
| 120101 | 120101 | 51.215130:0.007352 51.361517:0.007893 52.89855... | C=1C=CC2=C(C1)NC(=C2CN(C)C)C | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | AJNMXMZCRHTBEH | NaN | valid | ... | 0 | 2 | Organic compounds | Organoheterocyclic compounds | Indoles and derivatives | Indoles | 1 | 14 | 124 | 237 |
| 120551 | 120551 | 50.057374:0.014687 50.554329:0.015111 50.80970... | O=C1OC2C(C1=C)CCC3(C)C(O)CCC(=C)C23 | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | FKBUODICGDOIGB | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Prenol lipids | Terpene lactones | 1 | 6 | 198 | 447 |
| 124855 | 124855 | 51.399748:0.018784 51.908693:0.024215 51.93020... | O1C2=CC=C(C=C2OC1)C3OCC4C(OCC34)C5=CC=C6OCOC6=C5 | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | PEYUIKBAABKQKQ | NaN | train | ... | 0 | 2 | Organic compounds | Lignans, neolignans and related compounds | Furanoid lignans | NaN | 1 | 5 | 99 | -1 |
| 125729 | 125729 | 51.202819:0.069772 53.385390:0.050123 54.10081... | O=C(OC1CCC2(C)C(CCC3(C)C2CC=C4C5C(C)C(C)CCC5(C... | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | HLBZSQOUBVLLLL | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Prenol lipids | Triterpenoids | 1 | 6 | 198 | 467 |
2020 rows × 31 columns
from scipy import stats
from specvae.jointvae import JointVAE
from specvae.vae import SpecVEA
# cc = model.config['cont_capacity']
# cols, vals = ['model_name', 'min_capacity', 'max_capacity', 'num_iter', 'gamma_z'], [model_name] + cc
from sklearn.metrics import r2_score, mean_squared_error, explained_variance_score
from sklearn.linear_model import LinearRegression
for model_path in model_dirs:
print("-------------------------------------------")
print(model_path)
model = load_model(model_path, device)
data = preload_data_as_tensor(df, input_columns=model.config['input_columns'], types=model.config['types'], transform=model.transform)
data_np = evaluate_model(model, df, data)
for target_column in labels:
print(target_column)
if isinstance(model, SpecVEA):
n_dim = data_np['z'].shape[1]
elif isinstance(model, JointVAE):
n_dim = model.config['latent_spec']['cont']
def plot_reg(df, ax, data_np, dim=0):
df['z'] = data_np['z'][:,dim]
slope, intercept, r_value, p_value, std_err = stats.linregress(df[target_column], df['z'])
x, y = df[target_column].to_numpy().reshape(-1,1), df['z'].to_numpy().reshape(-1,1)
reg = LinearRegression().fit(x, y)
y_ = reg.predict(x)
r2_value = r2_score(y, y_)
rmse_value = mean_squared_error(y, y_, squared=False)
exp_variance_value = explained_variance_score(y, y_)
pearson_value, pp = stats.pearsonr(df[target_column], df['z'])
spearman_value, sp = stats.spearmanr(df[target_column], df['z'])
print("r^2", r2_value)
print("RMSE", rmse_value)
print("explained variance", exp_variance_value)
print("Pearson", pearson_value, "p=", pp)
print("Spearman", spearman_value, "p=", sp)
print("-----------------")
if target_column == 'collision_energy':
sns.boxplot(x=target_column, y='z', data=df, ax=ax)
else:
sns.regplot(x=target_column, y='z',
data=df, color='blue', scatter_kws={'s': 5}, ax=ax,
line_kws={'label':"z[{0}] = {1:.2f} + {2:.3f}*10^-3 * {3}".format(dim, intercept, slope * 1000., target_column)})
ax.legend(fontsize=16)
fig, axs = plt.subplots(1, n_dim, figsize=(15 * n_dim, 10))
if n_dim == 1:
plot_reg(df, axs, data_np, 0)
else:
for dim, ax in enumerate(axs):
plot_reg(df, ax, data_np, dim)
sns.despine(right = True)
plt.show()
plt.clf()
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_20-800-200-50-3-50-200-800-20_01 (24-12-2021_01-50-12) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -4.147547416621933e-09 RMSE 0.664303077446825 explained variance -1.0188360821672404e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.1425840718004565e-08 RMSE 0.7824517928029603 explained variance 4.7832540928105516e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -2.584761493729104e-08 RMSE 0.5377247045512953 explained variance -1.39494702455778e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
total_exact_mass r^2 0.04287237338309713 RMSE 0.649906962198283 explained variance 0.04287236760126767 Pearson 0.20705645933616637 p= 5.336316971653101e-21 Spearman 0.23250008050801355 p= 3.3682239599386913e-26 ----------------- r^2 0.006660683118936417 RMSE 0.7798416118681303 explained variance 0.00666071928314349 Pearson -0.08161293873644945 p= 0.00024075255569202278 Spearman -0.07078925190482395 p= 0.001454527588149293 ----------------- r^2 0.04715755133557631 RMSE 0.5248926993316515 explained variance 0.04715756267263316 Pearson 0.2171579516487489 p= 5.504075455824221e-23 Spearman 0.24839934157367277 p= 8.766254352946442e-30 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_20-400-100-3-400-20_02 (24-12-2021_03-34-34) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -3.6947340742443657e-09 RMSE 0.575849561488775 explained variance -7.4977525965636e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 4.1068646261521735e-09 RMSE 0.4373118601582907 explained variance 1.9030944597986377e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -2.7252179624071005e-08 RMSE 0.7190397377663857 explained variance 1.0537313255287728e-07 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.06311685877862572 RMSE 0.5573804754653673 explained variance 0.06311679199497988 Pearson -0.25123069525867997 p= 1.8915136167960563e-30 Spearman -0.2774695072394187 p= 4.980273392544591e-37 ----------------- r^2 0.06681632977168328 RMSE 0.4224495209425519 explained variance 0.06681634369859091 Pearson -0.2584885412145461 p= 3.39522257607939e-32 Spearman -0.2732499067394259 p= 6.392618278599651e-36 ----------------- r^2 0.0017724804542273986 RMSE 0.7184022034116205 explained variance 0.0017726128444601752 Pearson 0.042101159818969565 p= 0.05850705806282815 Spearman 0.059668841438603265 p= 0.0073071714544657275 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_20-1600-3-1600-20_03 (24-12-2021_00-17-31) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -5.0956425745596334e-09 RMSE 0.1810380104357133 explained variance 2.948580490880204e-09 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -5.004691994159316e-09 RMSE 0.3394804898056683 explained variance 6.728290591340169e-09 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -2.3316085062674574e-08 RMSE 0.708820351174095 explained variance 7.17245546288936e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.007111834738948497 RMSE 0.18039310511013892 explained variance 0.007111842725962436 Pearson 0.08433172474431977 p= 0.0001478491457300463 Spearman 0.070228965303993 p= 0.0015866725347411545 ----------------- r^2 0.12035317428627468 RMSE 0.3183970160323094 explained variance 0.1203531846071555 Pearson -0.3469195565093383 p= 3.271539478410464e-58 Spearman -0.3782896853472856 p= 9.89143138519233e-70 ----------------- r^2 0.002379715358625134 RMSE 0.7079764452242554 explained variance 0.0023798101730929666 Pearson -0.04878256470527226 p= 0.028346900796013118 Spearman -0.06634862149862297 p= 0.0028502644676080286 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_20-800-3-800-20_04 (24-12-2021_00-25-10) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 2.859744774319495e-09 RMSE 0.0023546095092869743 explained variance 1.493976620192683e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -8.66963434376089e-09 RMSE 0.012484113214707335 explained variance -2.752501893077408e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.22394405113846e-08 RMSE 0.7131784626591761 explained variance -7.629237197548377e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.07353929011424976 RMSE 0.002266378268854203 explained variance 0.07353930130591513 Pearson 0.27118128155314947 p= 2.197600626618897e-35 Spearman 0.2707745925024175 p= 2.7978817688333353e-35 ----------------- r^2 0.1650553695347171 RMSE 0.011407396436600974 explained variance 0.16505535379151526 Pearson -0.4062700786095155 p= 3.909501376244553e-81 Spearman -0.4381335171663226 p= 1.6074731241010572e-95 ----------------- r^2 0.0021208490822246517 RMSE 0.7124217972266675 explained variance 0.002120750759381118 Pearson 0.046052436308517214 p= 0.0384882761677196 Spearman 0.06496462222308022 p= 0.0034882554894263063 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_20-100-3-90-100-20_05 (24-12-2021_03-01-19) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 1.882175981737788e-08 RMSE 0.00634819113618062 explained variance 1.2186476683329062e-07 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.8071816265674556e-09 RMSE 0.008549702921341109 explained variance 1.0827333851715082e-07 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.830468859293944e-09 RMSE 0.6567552876814632 explained variance 3.223405131702606e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.0023579715834474158 RMSE 0.006340702351473486 explained variance 0.002358074383483899 Pearson -0.04855875622447877 p= 0.029081412583070843 Spearman -0.04525085703624098 p= 0.04199639627699957 ----------------- r^2 0.0012794480958832066 RMSE 0.008544231727910459 explained variance 0.0012795544258225044 Pearson 0.03576934848461674 p= 0.10802115109879161 Spearman 0.05369028262639267 p= 0.015807710849984998 ----------------- r^2 0.00231299275992336 RMSE 0.6559953137886534 explained variance 0.002313022095495665 Pearson -0.048093553996364925 p= 0.03066065725676492 Spearman -0.06976256159914165 p= 0.0017050041787833002 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_50-400-3-100-400-50_06 (24-12-2021_06-19-49) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -2.733259152343237e-08 RMSE 0.5892847459574868 explained variance -1.0607890121860919e-09 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.6614223108391002e-08 RMSE 0.0049758850112530915 explained variance -3.640402179705404e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.4110319579430097e-09 RMSE 0.014748428844789836 explained variance -1.6228465904433165e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.013888136867141965 RMSE 0.585178397152903 explained variance 0.013888162774077228 Pearson -0.11784805395140716 p= 1.0851688195350143e-07 Spearman -0.1540552931844876 p= 3.373084242585501e-12 ----------------- r^2 0.006890891974887903 RMSE 0.004958711190204801 explained variance 0.006890872321458796 Pearson -0.08301149603894645 p= 0.00018768457720912902 Spearman -0.05015945695414182 p= 0.024170331836321658 ----------------- r^2 0.008643231990494993 RMSE 0.014684553466487534 explained variance 0.0086432173011316 Pearson -0.09296899154735017 p= 2.852713711057548e-05 Spearman -0.12188042508109714 p= 3.908217766865297e-08 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_01 (24-12-2021_09-13-36) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -6.824412146499981e-10 RMSE 0.4024398033006996 explained variance 3.1536797617803813e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.5174451412368626e-09 RMSE 1.0143814892126788 explained variance -3.979500728945595e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.4464935632906304e-09 RMSE 0.6332436434900612 explained variance 1.863486664976932e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.2670899785614136 RMSE 0.3445293762951458 explained variance 0.2670900021752167 Pearson 0.5168074874279414 p= 2.3530144870200522e-138 Spearman 0.5659422522190873 p= 2.0434443340088012e-171 ----------------- r^2 0.0007131036771842458 RMSE 1.014019746402275 explained variance 0.0007130613949047904 Pearson 0.02670395404306305 p= 0.23026967312952232 Spearman 0.05375438059538423 p= 0.015682993943568 ----------------- r^2 0.054966001338144554 RMSE 0.6155942520567964 explained variance 0.05496601663670764 Pearson -0.2344482864644673 p= 1.2653731104172235e-26 Spearman -0.24551323625446897 p= 4.1023559367456404e-29 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_02 (24-12-2021_09-15-11) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -7.850753380722608e-10 RMSE 0.9537015085757884 explained variance -8.023315700711464e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 3.38479577699502e-10 RMSE 0.452179005294942 explained variance -8.090827630091724e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -3.833569017785976e-10 RMSE 0.4303479616769854 explained variance -1.6737302654945552e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.0029151828843919647 RMSE 0.9523103864611251 explained variance 0.0029151036679159192 Pearson 0.053992440833683514 p= 0.015227334381913819 Spearman 0.07621237187666009 p= 0.0006076277963196566 ----------------- r^2 0.17041973521768983 RMSE 0.41185050247228044 explained variance 0.17041966781698448 Pearson -0.4128192521393519 p= 5.76451980251651e-84 Spearman -0.45361834359281705 p= 4.344431109557457e-103 ----------------- r^2 0.175064644395154 RMSE 0.3908676330152114 explained variance 0.175064630904206 Pearson -0.4184072713414512 p= 1.9702237232531365e-86 Spearman -0.44827118328662136 p= 1.9759286864262323e-100 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_03 (24-12-2021_09-29-26) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -9.73681135718607e-10 RMSE 0.40851198808033 explained variance 5.1606942830240143e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 4.991126067999119e-09 RMSE 0.9485616663277566 explained variance 1.306082231256056e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -2.0062480565741225e-09 RMSE 0.3815903135936529 explained variance -3.2584164255666792e-09 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.2012375842965174 RMSE 0.3651014993080108 explained variance 0.20123762629594344 Pearson -0.4485951237744981 p= 1.3680495229824303e-100 Spearman -0.49040442207097285 p= 1.0297792718996563e-122 ----------------- r^2 0.0018718121840319846 RMSE 0.9476734882291372 explained variance 0.0018718202386232008 Pearson 0.04326438722839299 p= 0.05187144975100108 Spearman 0.06587630834700443 p= 0.003054919135910296 ----------------- r^2 0.15234064702051275 RMSE 0.3513241633042105 explained variance 0.15234064595910035 Pearson -0.3903084020631989 p= 1.7067868344089204e-74 Spearman -0.41299442342653214 p= 4.832381340853288e-84 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_04 (24-12-2021_09-29-36) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 1.7235308957808115e-08 RMSE 0.5241724901717993 explained variance 7.117885525431689e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.4960227773540566e-08 RMSE 0.06892836718321015 explained variance -8.394730244276616e-09 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -4.6642461004609e-09 RMSE 0.5223800269311212 explained variance -3.852154728534174e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.03018724788962268 RMSE 0.5162002057642239 explained variance 0.03018730020476279 Pearson -0.17374472991892523 p= 3.723495313935521e-15 Spearman -0.22705569366166364 p= 4.954659431759439e-25 ----------------- r^2 0.12815479191202195 RMSE 0.06436024499868441 explained variance 0.12815476283166094 Pearson -0.35798710891674074 p= 3.957838221445053e-62 Spearman -0.4016548487737466 p= 3.545337200992162e-79 ----------------- r^2 0.06390183378625969 RMSE 0.5054139906124394 explained variance 0.06390180209250218 Pearson 0.25278812897850256 p= 8.069740762568796e-31 Spearman 0.24818640631073888 p= 9.83016645185103e-30 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_05 (24-12-2021_09-06-14) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -2.731850301529448e-09 RMSE 0.5167635207564404 explained variance -8.22594830029999e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 5.337601471921971e-09 RMSE 0.266386036198035 explained variance -2.895975015348995e-09 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -8.072156276739406e-10 RMSE 0.005022425340842254 explained variance -3.11676371378411e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.024464701193467553 RMSE 0.5104031454496698 explained variance 0.024464623611455072 Pearson -0.15641196839910965 p= 1.5600672250830148e-12 Spearman -0.21851025947328 p= 2.930962159335559e-23 ----------------- r^2 0.12950171891125006 RMSE 0.24853949738025646 explained variance 0.129501711743936 Pearson 0.3598634661435875 p= 8.273438212991471e-63 Spearman 0.3492616966477554 p= 4.99834327337358e-59 ----------------- r^2 0.10282884595637709 RMSE 0.0047571970429824365 explained variance 0.10282881871788285 Pearson 0.32066937284466046 p= 1.5584439514989814e-49 Spearman 0.30847730182702554 p= 8.709001076865328e-46 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_06 (24-12-2021_09-05-10) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -2.5925022351103166e-08 RMSE 0.006721220655493831 explained variance -3.400042025702987e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 4.7443513562228645e-09 RMSE 0.002071929663549238 explained variance 5.2055799781847156e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.4442340373909133e-09 RMSE 0.5322316435398884 explained variance -5.060269914203275e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.013215037885437986 RMSE 0.006676662276681685 explained variance 0.013215029916756937 Pearson 0.11495678956833985 p= 2.2111427839122324e-07 Spearman 0.1338472294911072 p= 1.5492534917073538e-09 ----------------- r^2 0.020762989878398308 RMSE 0.002050307115159944 explained variance 0.020763036207519625 Pearson 0.14409366825975967 p= 7.708771816038071e-11 Spearman 0.18793065998725328 p= 1.63457518098644e-17 ----------------- r^2 0.03029183636575683 RMSE 0.5241085181002526 explained variance 0.030291784925712495 Pearson -0.17404549403981423 p= 3.333925626014178e-15 Spearman -0.2397147572213658 p= 8.576103837738748e-28 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-400-100-3-400-100_01 (24-12-2021_11-06-17) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 1.1448291203919325e-09 RMSE 0.9496722590600737 explained variance -6.206346281345532e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -2.589102043870639e-08 RMSE 0.34657070373220583 explained variance 3.457135111517573e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.0922913684652258e-09 RMSE 0.3791727176699963 explained variance -1.2725853637540752e-07 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.01578798552932592 RMSE 0.9421457282766297 explained variance 0.01578792331896539 Pearson 0.12565024632913124 p= 1.4595647220168722e-08 Spearman 0.1430118110780733 p= 1.0692756762975772e-10 ----------------- r^2 0.2971785514771361 RMSE 0.29054562879285933 explained variance 0.2971785939713868 Pearson 0.5451408714028882 p= 9.528189247608974e-157 Spearman 0.5890722585364071 p= 5.274029781520154e-189 ----------------- r^2 0.016989219875928163 RMSE 0.3759379954238541 explained variance 0.016989095853149228 Pearson 0.13034270577850643 p= 4.111386998309379e-09 Spearman 0.1317327161697762 p= 2.80023715567139e-09 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-800-100-3-800-100_02 (24-12-2021_10-59-29) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -7.644120669780818e-09 RMSE 0.37896445211905744 explained variance -1.56231303449772e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -5.618870035917212e-09 RMSE 0.9716767595767878 explained variance 2.918713060129363e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 5.40974087748225e-09 RMSE 0.7172091485612855 explained variance -8.5350509326787e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.037214440958276085 RMSE 0.3718461215426054 explained variance 0.037214433276200776 Pearson 0.19291046710307125 p= 2.187789759353354e-18 Spearman 0.20194821669958188 p= 4.9357080243886025e-20 ----------------- r^2 0.031071879941588887 RMSE 0.9564617225089959 explained variance 0.031071913666101403 Pearson -0.17627219118700996 p= 1.4620421816954826e-15 Spearman -0.1950614938993849 p= 9.022191309335799e-19 ----------------- r^2 0.17556303169250265 RMSE 0.651215232699109 explained variance 0.17556295686639667 Pearson -0.4190024191248926 p= 1.0692577650883482e-86 Spearman -0.43618821289674525 p= 1.3472871567851266e-94 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-400-200-50-3-50-200-400-100_03 (24-12-2021_09-47-19) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 5.524619650643103e-10 RMSE 0.39394038723622254 explained variance 5.559138216426618e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -3.450831753681882e-08 RMSE 0.3712022821567741 explained variance -5.306525197035228e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.251015069314576e-09 RMSE 0.9628091423506911 explained variance 3.418955540901436e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.07721568198649542 RMSE 0.37842568898975515 explained variance 0.07721573277554794 Pearson 0.2778770977908981 p= 3.88282624764978e-37 Spearman 0.3172923175810199 p= 1.7712008934569286e-48 ----------------- r^2 0.27757783395716296 RMSE 0.315504938553781 explained variance 0.2775778205512226 Pearson 0.5268565828446443 p= 1.1151746694987933e-144 Spearman 0.5742015936233861 p= 1.5512582400055316e-177 ----------------- r^2 0.003317404471161467 RMSE 0.9612108013860218 explained variance 0.0033174397941612144 Pearson 0.05759692455354254 p= 0.009619725373517773 Spearman 0.08098337296902282 p= 0.0002689740021599073 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-1600-3-1600-100_04 (24-12-2021_08-02-44) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -1.7453098966058178e-09 RMSE 0.5006161964004462 explained variance 1.655688131041444e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 9.599339101384885e-10 RMSE 0.7234964015113673 explained variance -1.1952944634074925e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.1465888016815029e-08 RMSE 0.12764011728275243 explained variance 3.986427421498462e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.06736980109210078 RMSE 0.48345898151588657 explained variance 0.06736981816127707 Pearson 0.25955693541076796 p= 1.85833707753681e-32 Spearman 0.3106631114079365 p= 1.9100530013201946e-46 ----------------- r^2 0.009686333584385642 RMSE 0.7199838615033309 explained variance 0.009686320796585601 Pearson -0.09841916802000546 p= 9.36165493856104e-06 Spearman -0.08357250993520207 p= 0.00016966099395763023 ----------------- r^2 0.02539156556223887 RMSE 0.12600920594717288 explained variance 0.025391615589047345 Pearson 0.15934734618747126 p= 5.872455469610849e-13 Spearman 0.19950869618109882 p= 1.398566123170853e-19 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-400-100-3-400-100_05 (24-12-2021_10-57-01) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 1.7059998969060075e-09 RMSE 0.5563992987912569 explained variance 8.778219584559821e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.7970413762901103e-09 RMSE 0.2830884970874378 explained variance 4.203167913718886e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.703778312351801e-10 RMSE 0.0052383411076949524 explained variance 5.712315731543072e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.020201745436497 RMSE 0.550750506337021 explained variance 0.020201829773803914 Pearson 0.14213283844685967 p= 1.3923794722266486e-10 Spearman 0.20511632148516637 p= 1.2508404760586714e-20 ----------------- r^2 0.11424980438838206 RMSE 0.2664267651808323 explained variance 0.11424983914047038 Pearson -0.3380085825994691 p= 3.596716971773298e-55 Spearman -0.3320525701809953 p= 3.4160295839186984e-53 ----------------- r^2 0.13363840258285786 RMSE 0.0048757718082037315 explained variance 0.1336384518379229 Pearson 0.36556586595114826 p= 6.661368857472203e-65 Spearman 0.3699862494827164 p= 1.4815884116853483e-66 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-400-100-3-100-400-100_06 (24-12-2021_08-41-33) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -1.1152351708787478e-08 RMSE 0.5094651228082928 explained variance -1.0477918754858706e-07 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 4.5837340589827136e-09 RMSE 0.0034353416856058015 explained variance -1.436039620550389e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.3691114908453983e-10 RMSE 0.006307373968703753 explained variance -4.8544401831662753e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.03207329886647525 RMSE 0.5012284237018838 explained variance 0.0320732082425621 Pearson -0.17909022770976166 p= 5.071532068024876e-16 Spearman -0.24116789294759985 p= 4.0337452609939e-28 ----------------- r^2 0.13361926016010783 RMSE 0.003197601469534873 explained variance 0.1336192437472783 Pearson 0.3655396779952199 p= 6.812057920298084e-65 Spearman 0.35877458181335786 p= 2.0546011245494524e-62 ----------------- r^2 0.03796821470932732 RMSE 0.006186475423576089 explained variance 0.037968168139782765 Pearson -0.19485434262812815 p= 9.830032451358511e-19 Spearman -0.2013021004436663 p= 6.512077254810348e-20 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-100-90-50-3-50-90-100-100_01 (24-12-2021_09-48-37) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -5.20971266126935e-10 RMSE 0.4724469569588173 explained variance 2.4688966981933902e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.9337067502789296e-09 RMSE 0.615774836518459 explained variance -1.598906340660733e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -4.030078493144629e-09 RMSE 0.849190913355075 explained variance -3.027930839394344e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.12815104968161728 RMSE 0.44113719810275603 explained variance 0.12815107166087558 Pearson -0.35798191314063016 p= 3.974971577435081e-62 Spearman -0.39717518384377176 p= 2.631883238991292e-77 ----------------- r^2 0.024207090496919603 RMSE 0.6082761187947601 explained variance 0.024207076781802228 Pearson 0.15558628597603627 p= 2.0467200514601947e-12 Spearman 0.20276606287620347 p= 3.47055465791067e-20 ----------------- r^2 0.007587582916154467 RMSE 0.845963123981879 explained variance 0.007587556866092804 Pearson -0.0871067558554117 p= 8.85522414786485e-05 Spearman -0.0684668240385073 p= 0.00207759700910438 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-1600-100-3-1600-100_02 (24-12-2021_10-51-41) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 5.123414248409119e-09 RMSE 0.41132537063043734 explained variance -8.682255359104829e-09 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 4.747906734436924e-09 RMSE 0.9727648198862009 explained variance 2.6120321461320373e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -3.585601193734078e-08 RMSE 0.4237430480348816 explained variance -7.149246084026117e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
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total_exact_mass r^2 0.01715959543095691 RMSE 0.4077810124638873 explained variance 0.017159581862186912 Pearson 0.1309946197195081 p= 3.4354141448966727e-09 Spearman 0.1354866714822288 p= 9.728048259994415e-10 ----------------- r^2 0.017357229866493462 RMSE 0.9642856159392219 explained variance 0.017357250867942375 Pearson 0.1317468223563562 p= 2.7892871292837338e-09 Spearman 0.15204991463504972 p= 6.4408820846983634e-12 ----------------- r^2 0.28738091032545865 RMSE 0.3577101838096063 explained variance 0.28738088493024583 Pearson -0.5360792253735789 p= 1.1293241739825248e-150 Spearman -0.5727386580083541 p= 1.9379540080969837e-176 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-800-100-3-800-100_03 (24-12-2021_11-16-41) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 6.301411614728636e-10 RMSE 0.9746381904331268 explained variance 4.081098259334226e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 7.410817515207668e-10 RMSE 0.37769938295648314 explained variance -4.1031641417887954e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -7.569411764052347e-11 RMSE 0.33907888942924735 explained variance -1.703310914535905e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.015283077065721407 RMSE 0.9671617798242222 explained variance 0.015283116632475946 Pearson 0.12362474042525076 p= 2.486754845037869e-08 Spearman 0.14893135151226808 p= 1.7315322202722254e-11 ----------------- r^2 0.0050186582630454835 RMSE 0.3767504189021216 explained variance 0.005018616699965284 Pearson -0.07084248390396164 p= 0.00144251501538648 Spearman -0.06820845207757356 p= 0.002160282529585145 ----------------- r^2 0.30554476501036143 RMSE 0.2825679364794657 explained variance 0.30554475323419583 Pearson -0.5527610379385722 p= 5.314413265669158e-162 Spearman -0.5981218082797555 p= 2.7919474558567817e-196 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-1600-3-1600-100_04 (24-12-2021_08-02-44) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -1.7453098966058178e-09 RMSE 0.5006161964004462 explained variance 1.655688131041444e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 9.599339101384885e-10 RMSE 0.7234964015113673 explained variance -1.1952944634074925e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.1465888016815029e-08 RMSE 0.12764011728275243 explained variance 3.986427421498462e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
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total_exact_mass r^2 0.06736980109210078 RMSE 0.48345898151588657 explained variance 0.06736981816127707 Pearson 0.25955693541076796 p= 1.85833707753681e-32 Spearman 0.3106631114079365 p= 1.9100530013201946e-46 ----------------- r^2 0.009686333584385642 RMSE 0.7199838615033309 explained variance 0.009686320796585601 Pearson -0.09841916802000546 p= 9.36165493856104e-06 Spearman -0.08357250993520207 p= 0.00016966099395763023 ----------------- r^2 0.02539156556223887 RMSE 0.12600920594717288 explained variance 0.025391615589047345 Pearson 0.15934734618747126 p= 5.872455469610849e-13 Spearman 0.19950869618109882 p= 1.398566123170853e-19 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-400-200-50-3-50-200-400-100_05 (24-12-2021_09-23-23) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 8.990671540587414e-10 RMSE 0.5128058516418403 explained variance 3.8086960141292536e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 3.9121729189517396e-09 RMSE 0.26405269223919775 explained variance -3.015199090405929e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 6.236624550126635e-10 RMSE 0.013102170589854358 explained variance -6.489591641845038e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.024235026295944984 RMSE 0.5065538082825439 explained variance 0.024235062582588562 Pearson 0.15567602711614495 p= 1.9873446308050103e-12 Spearman 0.21905765055187884 p= 2.2683482551542563e-23 ----------------- r^2 0.11298634142220476 RMSE 0.24868852950125772 explained variance 0.11298631120682623 Pearson -0.3361344045944331 p= 1.5237815827121363e-54 Spearman -0.32781771998892 p= 8.187943214740212e-52 ----------------- r^2 0.12673842622031206 RMSE 0.01224377739070846 explained variance 0.12673836900458135 Pearson 0.3560034068315801 p= 2.0471621595643034e-61 Spearman 0.35238986802738514 p= 3.9644409666774855e-60 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-1600-100-3-100-1600-100_06 (24-12-2021_08-25-38) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -6.195821633525611e-11 RMSE 0.004197744664064381 explained variance 6.943339481146893e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.3763146178291663e-10 RMSE 0.0017403750564796703 explained variance 3.371977908006585e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 6.650752171211138e-10 RMSE 0.5023463853625675 explained variance -4.285004640003365e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 3.390201066089116e-05 RMSE 0.004197673507339072 explained variance 3.397150365791468e-05 Pearson 0.0058225486358624776 p= 0.7936828562496234 Spearman -0.11205902213929267 p= 4.4361922770439525e-07 ----------------- r^2 0.03682908172271515 RMSE 0.0017080262101678582 explained variance 0.03682911433318836 Pearson -0.1919090457880443 p= 3.292835261554696e-18 Spearman -0.214074088891931 p= 2.2799938718831643e-22 ----------------- r^2 0.03420322494999406 RMSE 0.49368070912115947 explained variance 0.03420318292322999 Pearson 0.18494113741314172 p= 5.3240586027011415e-17 Spearman 0.2470306792530434 p= 1.8269920494362957e-29 -----------------
<Figure size 432x288 with 0 Axes>
<Figure size 432x288 with 0 Axes>
# df2 = pd.DataFrame([vals], columns=cols)
# df2
# stats_file = "d:\\Workspace\\SpecVAE\\.model\\MoNA\\joint_vae_%d_stats.csv" % n_dim
# if os.path.exists(stats_file):
# df = pd.read_csv(stats_file, index_col=0)
# df = pd.concat([df, df2], ignore_index=True)
# df.to_csv(stats_file)
# else:
# df2.to_csv(stats_file)